{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = np.genfromtxt(\"Arrhenius.dat\", dtype=str)\n",
    "Header = (data[0,:]).tolist()\n",
    "solTchem = (data[1:,:]).astype(np.float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "campsol = np.loadtxt(\"rxn_arrhenius_results.txt\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "A_indx = Header.index('A')\n",
    "B_indx = Header.index('B')\n",
    "C_indx = Header.index('C')\n",
    "t_indx = Header.index('t')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of Cells: 5\n",
      "Number of time iterations: 501.0\n"
     ]
    }
   ],
   "source": [
    "niterT, Nvars = np.shape(solTchem)\n",
    "Nsamples = len(np.where(solTchem[:,0]==-1)[0])\n",
    "print('Number of Cells:',Nsamples)\n",
    "print('Number of time iterations:',niterT/Nsamples)\n",
    "solTchem = solTchem.reshape( int(niterT/Nsamples), Nsamples,Nvars)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x117b1bad0>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sp=0 # cell number 0, camp only saved cell No 1 \n",
    "plt.figure()\n",
    "plt.plot(solTchem[:,sp,t_indx],solTchem[:,sp,A_indx], label=\"A\")\n",
    "plt.plot(solTchem[:,sp,t_indx],solTchem[:,sp,B_indx], label=\"B\")\n",
    "plt.plot(solTchem[:,sp,t_indx],solTchem[:,sp,C_indx], label=\"C\")\n",
    "plt.xlabel('Time [s]')\n",
    "plt.ylabel('Concentration [mol/m3]')\n",
    "plt.legend(loc='best')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x117bdfa10>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(campsol[:,0],campsol[:,1],label='CAMP')\n",
    "plt.plot(solTchem[:,sp,t_indx],solTchem[:,sp,A_indx],\"*\",label='TChem')\n",
    "plt.xlabel('Time [s]')\n",
    "plt.ylabel('Concentration of A [mol/m3]')\n",
    "plt.legend(loc='best')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x117cb7290>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(campsol[:,0],campsol[:,3],label='CAMP')\n",
    "plt.plot(solTchem[:,sp,t_indx],solTchem[:,sp,B_indx],\"*\",label='TChem')\n",
    "plt.xlabel('Time [s]')\n",
    "plt.ylabel('Concentration of B [mol/m3]')\n",
    "plt.legend(loc='best')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x117cd8810>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(campsol[:,0],campsol[:,5],label='CAMP')\n",
    "plt.plot(solTchem[:,sp,t_indx],solTchem[:,sp,C_indx],\"*\",label='TChem')\n",
    "plt.xlabel('Time [s]')\n",
    "plt.ylabel('Concentration of B [mol/m3]')\n",
    "plt.legend(loc='best')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
